Cardiovascular and Respiratory Bioengineering focuses on computational tools and modeling techniques in cardiovascular and respiratory systems that help develop bioengineered solutions. The book demonstrates how these technologies can be utilized in order to tackle diseases and medical issues. It provides practical guidance on how a bioengineering or medical problem can be modeled, along with which computational models can be used. Topics include computer modeling of Purkinje fibers with different electrical potential applied, modeling of cardiomyopathies caused by sarcomeric gene mutations, altered sarcomere function, perturbations in intracellular ion homeostasis, impaired myocardial energetics at reduced costs, and more.
The book also discusses blood flow through deformable blood vessels in human aorta, abdominal aortic aneurysm, carotid artery, coronary artery and plaque formation, along with content on stent deployment modeling and stent design and optimization techniques.
- Features practical applications of cardiovascular and respiratory technology to counteract diseases
- Includes detailed steps for the modeling of cardiovascular and respiratory systems
- Explores a range of different modeling methods, including computational modeling, predictive modeling and multi-scale modeling
- Covers biological processes and biomechanics relevant to cardiovascular and respiratory bioengineering
| Contributors |
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ix | |
| Preface |
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xi | |
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1 Computational modeling of electromechanical coupling of left ventricle |
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1 | (2) |
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3 | (7) |
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10 | (13) |
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21 | (2) |
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2 Deep learning approach in ultrasound image segmentation for patients with carotid artery disease |
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23 | (2) |
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2 Carotid artery and personalized medicine |
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25 | (2) |
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3 Previous approaches in medical image segmentation |
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27 | (2) |
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4 Dataset acquisition and description |
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29 | (1) |
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30 | (4) |
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34 | (2) |
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36 | (5) |
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37 | (1) |
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37 | (4) |
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3 Simulation of stent mechanical testing |
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41 | (3) |
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44 | (3) |
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47 | (15) |
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62 | (5) |
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63 | (4) |
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4 ECG simulation of cardiac hypertrophic condition |
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67 | (1) |
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68 | (6) |
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74 | (4) |
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78 | (9) |
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87 | (2) |
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89 | (3) |
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92 | (3) |
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95 | (6) |
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96 | (5) |
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5 Simulation of carotid artery plaque development and treatment |
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101 | (2) |
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103 | (14) |
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117 | (7) |
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4 Discussion and conclusions |
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124 | (11) |
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129 | (1) |
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129 | (6) |
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6 Myocardial work and aorta stenosis simulation |
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135 | (1) |
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136 | (2) |
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138 | (1) |
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4 Computational simulation of myocardial work in aortic stenosis |
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139 | (2) |
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5 Computational simulation of patient-specific aortic root |
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141 | (2) |
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143 | (6) |
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144 | (1) |
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144 | (5) |
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7 Lab-on-a-chip for lung tissue from in silico perspective |
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149 | (2) |
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2 In silico lung-on-a-chip models |
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151 | (1) |
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3 Mathematical model for epithelial cell behavior and fluid flow |
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152 | (2) |
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4 Mason-Weaver equation, finite difference method |
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154 | (10) |
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164 | (5) |
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166 | (1) |
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166 | (3) |
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8 Chaotic mixing and its role in enhancing particle deposition in the pulmonary acinus: A review |
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169 | (1) |
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170 | (2) |
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3 Computational simulation and Hamiltonian chaos |
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172 | (3) |
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4 Proof of the occurrence of chaotic mixing in vivo |
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175 | (4) |
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5 Effects of acinar chaotic mixing on inhaled particle deposition |
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179 | (4) |
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6 Physiological significance |
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183 | (1) |
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184 | (3) |
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184 | (1) |
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184 | (3) |
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9 Three-dimensional reconstruction and modeling of the respiratory airways, particle deposition, and drug delivery efficacy |
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187 | (2) |
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189 | (9) |
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198 | (9) |
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207 | (6) |
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208 | (5) |
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10 Tissue engineering---Electrospinning approach |
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213 | (3) |
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2 Electrospinning in tissue engineering |
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216 | (5) |
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221 | (4) |
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221 | (4) |
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11 Application of numerical methods for the analysis of respiratory system |
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225 | (1) |
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2 Air transport and particle deposition |
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226 | (1) |
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3 Respiratory system models |
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227 | (4) |
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4 Numerical analysis of human respiratory system |
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231 | (1) |
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232 | (5) |
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232 | (1) |
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233 | (4) |
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12 Artificial intelligence approach toward analysis of COVID-19 development---Personalized and epidemiological model |
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237 | (5) |
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242 | (9) |
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251 | (14) |
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265 | (6) |
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265 | (1) |
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Conflict of interest statement |
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266 | (1) |
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266 | (1) |
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266 | (5) |
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13 Economic analysis for in silico clinical trials of biodegradable and metallic vascular stents |
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271 | (2) |
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273 | (8) |
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281 | (1) |
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4 Description of the modules |
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282 | (5) |
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287 | (3) |
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290 | (3) |
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290 | (1) |
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290 | (3) |
| Index |
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293 | |
Nenad D. Filipovic is Rector of University of Kragujevac, Serbia, full Professor at Faculty of Engineering and Head of Center for Bioengineering at University of Kragujevac, Serbia. He was Research Associate at Harvard School of Public Health in Boston, US. His research interests are in the area of biomedical engineering, cardiovascular disease, fluid-structure interaction, biomechanics, bioinformatics, biomedical image processing, medical informatics, multi-scale modeling, data mining, software engineering, parallel computing, computational chemistry and bioprocess modeling. He is author and co-author 16 textbooks and 11 monographies, over 300 publications in peer review journals and over 10 software for modeling with finite element method and discrete methods from biofluid mechanics and multiphysics. He also leads a number of national and international projects in EU and US in area of bioengineering and software development. He is Director of Center for Bioengineering at University of Kragujevac and leads joint research projects with Harvard University and University of Texas in area of bio-nano-medicine computer simulation. He also leads a number of national and international projects in area of bioengineering and bioinformatics. He is a Managing Editor for Journal of Serbian Society for Computational Mechanics and member of European Society of Biomechanics (ESB), European Society for Artificial Organs (ESAO) and IEEE member.
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